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Development of an integrated BLSVM-MFA method for analyzing renewable power-generation potential under climate change: A case study of Xiamen

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  • Wang, Bingqing
  • Li, Yongping
  • Huang, Guohe
  • Gao, Pangpang
  • Liu, Jing
  • Wen, Yizhuo

Abstract

In order to reduce fossil-energy carbon emission and mitigate its climate change impact, developing integrated mathematical methods that are capable of predicting renewable power-generation (e.g., wind and photovoltaic power) potential are desired. This study advances an integrated Bayesian least-squares-support-vector-machine based multilevel-factorial-analysis (BLSVM-MFA) method to find out the main factors affecting wind- and photovoltaic-power generations (WPG and PPG), as well as predict WPG and PPG potentials. The BLSVM-MFA method is then applied to a case study of Xiamen (China), where various factors including climate, economic, technological and capacity are investigated and 216 scenarios are analyzed. Results disclose that the main factors affecting WPG are wind power index (contributing 54.04%) > installed capacity (41.45%) > technology (2.60%), and the main factors affecting PPG are installed capacity (60.36%) > solar radiation (19.27%) > technology (9.24%). Results also reveal that WPG and PPG potentials (in 2020–2035) decrease under most scenarios and WPG and PPG show seasonal complementarity. Ensemble predictions under 216 scenarios indicate that WPG and PPG would be 130.21 WMh and 436.51 MWh by 2035. The promotion of high-conversion and high-profit technologies can improve the competitiveness of WPG and PPG in the regional power system. Results are valuable for revealing the impacts of climate change, economic development, and technological improvement on renewable power potentials and providing support for regional energy-structure transformation and carbon-emission abatement.

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  • Wang, Bingqing & Li, Yongping & Huang, Guohe & Gao, Pangpang & Liu, Jing & Wen, Yizhuo, 2023. "Development of an integrated BLSVM-MFA method for analyzing renewable power-generation potential under climate change: A case study of Xiamen," Applied Energy, Elsevier, vol. 337(C).
    • Handle: RePEc:eee:appene:v:337:y:2023:i:c:s0306261923002520
    DOI: 10.1016/j.apenergy.2023.120888
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    as
    1. Weipeng Zhang & Bo Zhao & Liming Zhou & Jizhong Wang & Kang Niu & Fengzhu Wang & Ruixue Wang, 2022. "Research on Comprehensive Operation and Maintenance Based on the Fault Diagnosis System of Combine Harvester," Agriculture, MDPI, vol. 12(6), pages 1-17, June.
    2. Zhu, Bangzhu & Ye, Shunxin & Jiang, Minxing & Wang, Ping & Wu, Zhanchi & Xie, Rui & Chevallier, Julien & Wei, Yi-Ming, 2019. "Achieving the carbon intensity target of China: A least squares support vector machine with mixture kernel function approach," Applied Energy, Elsevier, vol. 233, pages 196-207.
    3. Shi, Jing & Guo, Jinmei & Zheng, Songtao, 2012. "Evaluation of hybrid forecasting approaches for wind speed and power generation time series," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3471-3480.
    4. Nhuchhen, Daya R. & Sit, Song P. & Layzell, David B., 2022. "Towards net-zero emission cement and power production using Molten Carbonate Fuel Cells," Applied Energy, Elsevier, vol. 306(PB).
    5. Mills, Andrew D. & Rodriguez, Pía, 2020. "A simple and fast algorithm for estimating the capacity credit of solar and storage," Energy, Elsevier, vol. 210(C).
    6. Qunli Wu & Huaxing Lin, 2019. "Short-Term Wind Speed Forecasting Based on Hybrid Variational Mode Decomposition and Least Squares Support Vector Machine Optimized by Bat Algorithm Model," Sustainability, MDPI, vol. 11(3), pages 1-18, January.
    7. He, Gang & Kammen, Daniel M., 2016. "Where, when and how much solar is available? A provincial-scale solar resource assessment for China," Renewable Energy, Elsevier, vol. 85(C), pages 74-82.
    8. Liu, Da & Liu, Yumeng & Sun, Kun, 2021. "Policy impact of cancellation of wind and photovoltaic subsidy on power generation companies in China," Renewable Energy, Elsevier, vol. 177(C), pages 134-147.
    9. Yao, Huizong & Zang, Chuanfu, 2021. "The spatiotemporal characteristics of electrical energy supply-demand and the green economy outlook of Guangdong Province, China," Energy, Elsevier, vol. 214(C).
    10. Elena Verdolini & Marzio Galeotti, 2009. "At Home and Abroad: An Empirical Analysis of Innovation and Diffusion in Energy-Efficient Technologies," Working Papers 2009.123, Fondazione Eni Enrico Mattei.
    11. Yuan, Xiaohui & Tan, Qingxiong & Lei, Xiaohui & Yuan, Yanbin & Wu, Xiaotao, 2017. "Wind power prediction using hybrid autoregressive fractionally integrated moving average and least square support vector machine," Energy, Elsevier, vol. 129(C), pages 122-137.
    12. Wang, Heming & Wang, Guoqiang & Qi, Jianchuan & Schandl, Heinz & Li, Yumeng & Feng, Cuiyang & Yang, Xuechun & Wang, Yao & Wang, Xinzhe & Liang, Sai, 2020. "Scarcity-weighted fossil fuel footprint of China at the provincial level," Applied Energy, Elsevier, vol. 258(C).
    13. Gorjian, Shiva & Zadeh, Babak Nemat & Eltrop, Ludger & Shamshiri, Redmond R. & Amanlou, Yasaman, 2019. "Solar photovoltaic power generation in Iran: Development, policies, and barriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 106(C), pages 110-123.
    14. Wen-Chi Liu, 2020. "The Relationship between Primary Energy Consumption and Real Gross Domestic Product: Evidence from Major Asian Countries," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    15. Lin, Zhenjia & Chen, Haoyong & Wu, Qiuwei & Li, Weiwei & Li, Mengshi & Ji, Tianyao, 2020. "Mean-tracking model based stochastic economic dispatch for power systems with high penetration of wind power," Energy, Elsevier, vol. 193(C).
    16. Wang, Juan & Li, Ziming & Wu, Tong & Wu, Siyu & Yin, Tingwei, 2022. "The decoupling analysis of CO2 emissions from power generation in Chinese provincial power sector," Energy, Elsevier, vol. 255(C).
    17. Chandel, Rahul & Chandel, Shyam Singh & Malik, Prashant, 2022. "Perspective of new distributed grid connected roof top solar photovoltaic power generation policy interventions in India," Energy Policy, Elsevier, vol. 168(C).
    18. Li, M.S. & Lin, Z.J. & Ji, T.Y. & Wu, Q.H., 2018. "Risk constrained stochastic economic dispatch considering dependence of multiple wind farms using pair-copula," Applied Energy, Elsevier, vol. 226(C), pages 967-978.
    19. Martins, F.R. & Pereira, E.B. & Silva, S.A.B. & Abreu, S.L. & Colle, Sergio, 2008. "Solar energy scenarios in Brazil, Part one: Resource assessment," Energy Policy, Elsevier, vol. 36(8), pages 2843-2854, August.
    20. Liu, J. & Nie, S. & Shan, B.G. & Li, Y.P. & Huang, G.H. & Liu, Z.P., 2019. "Development of an interval-credibility-chance constrained energy-water nexus system planning model—a case study of Xiamen, China," Energy, Elsevier, vol. 181(C), pages 677-693.
    21. Mutschler, Robin & Rüdisüli, Martin & Heer, Philipp & Eggimann, Sven, 2021. "Benchmarking cooling and heating energy demands considering climate change, population growth and cooling device uptake," Applied Energy, Elsevier, vol. 288(C).
    22. Jia, Zhijie & Lin, Boqiang, 2021. "How to achieve the first step of the carbon-neutrality 2060 target in China: The coal substitution perspective," Energy, Elsevier, vol. 233(C).
    23. Gao, Yang & Ma, Shaoxiu & Wang, Tao, 2019. "The impact of climate change on wind power abundance and variability in China," Energy, Elsevier, vol. 189(C).
    24. Makowski, David & Naud, Cédric & Jeuffroy, Marie-Hélène & Barbottin, Aude & Monod, Hervé, 2006. "Global sensitivity analysis for calculating the contribution of genetic parameters to the variance of crop model prediction," Reliability Engineering and System Safety, Elsevier, vol. 91(10), pages 1142-1147.
    25. Zhao, Xiaohu & Huang, Guohe & Lu, Chen & Zhou, Xiong & Li, Yongping, 2020. "Impacts of climate change on photovoltaic energy potential: A case study of China," Applied Energy, Elsevier, vol. 280(C).
    26. Martins, F.R. & Rüther, R. & Pereira, E.B. & Abreu, S.L., 2008. "Solar energy scenarios in Brazil. Part two: Photovoltaics applications," Energy Policy, Elsevier, vol. 36(8), pages 2855-2867, August.
    27. Verdolini, Elena & Galeotti, Marzio, 2011. "At home and abroad: An empirical analysis of innovation and diffusion in energy technologies," Journal of Environmental Economics and Management, Elsevier, vol. 61(2), pages 119-134, March.
    28. Franke, Katja & Sensfuß, Frank & Deac, Gerda & Kleinschmitt, Christoph & Ragwitz, Mario, 2021. "Factors affecting the calculation of wind power potentials: A case study of China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    29. Popp, David & Hascic, Ivan & Medhi, Neelakshi, 2011. "Technology and the diffusion of renewable energy," Energy Economics, Elsevier, vol. 33(4), pages 648-662, July.
    30. Narayan, Paresh Kumar & Narayan, Seema & Prasad, Arti, 2008. "A structural VAR analysis of electricity consumption and real GDP: Evidence from the G7 countries," Energy Policy, Elsevier, vol. 36(7), pages 2765-2769, July.
    31. Jin, L. & Huang, G.H. & Fan, Y.R. & Wang, L. & Wu, T., 2015. "A pseudo-optimal inexact stochastic interval T2 fuzzy sets approach for energy and environmental systems planning under uncertainty: A case study for Xiamen City of China," Applied Energy, Elsevier, vol. 138(C), pages 71-90.
    32. Yan, Zheming & Du, Keru & Yang, Zhiming & Deng, Min, 2017. "Convergence or divergence? Understanding the global development trend of low-carbon technologies," Energy Policy, Elsevier, vol. 109(C), pages 499-509.
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    1. Weijie Zhou & Huimin Jiang & Jiaxin Chang, 2023. "Forecasting Renewable Energy Generation Based on a Novel Dynamic Accumulation Grey Seasonal Model," Sustainability, MDPI, vol. 15(16), pages 1-26, August.

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